Lead Data Engineer

We’re looking for a Senior Data Engineer to support the design, development, and optimization of data solutions for a high-impact enterprise initiative.

This role is ideal for someone with strong hands-on experience in data processing, transformation, and validation, who thrives in building reliable and well-structured datasets for analytics and business workflows.

You will work closely with cross-functional teams to ensure data is accurate, standardized, and ready for downstream consumption, contributing to scalable and high-quality data pipelines. What will you be doing? Design, develop, and maintain data pipelines to ingest, transform, and normalize data from multiple sources.

Lead the design and implementation of data ingestion architectures in Snowflake , ensuring scalability and reliability. Apply best practices in data validation to ensure accuracy, consistency, and reliability across datasets. Perform data transformation and normalization to support analytics and reporting use cases.

Work with large datasets using SQL and Python to process and analyze data efficiently. Ensure data quality by implementing validation rules, checks, and monitoring processes. Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable solutions.

Support ETL processes and file handling workflows for structured and semi-structured data. Contribute to documentation and continuous improvement of data processes and standards. What are we looking for? 4+ years of experience in Data Engineering or Data Analytics roles with strong engineering focus.

Strong hands-on experience with Snowflake (Must) . Strong hands-on experience with Python for data processing and transformation. Strong experience with SQL and working with large-scale datasets. Proven experience in data validation, data transformation, and normalization .

Experience building and maintaining ETL pipelines and handling data ingestion workflows. Strong attention to det